Strategic Design of “Three‐in‐One” Cathode Toward Optimal Performance of Proton‐Conducting Solid Oxide Fuel Cell: The Temperature Matters
Bibliographic record
Abstract
ABSTRACT “Three‐in‐one” cathode, achieved via B‐site heavy‐doping of transition elements (typically Co, Fe) into proton‐conductive perovskite, holds promise for enhancing the performance of proton‐conducting solid oxide fuel cell (H‐SOFC) operated below 650°C for electricity generation. However, its electrochemical behavior above 650°C, essential for improving the efficiency of H‐SOFC for fuel conversion, remains insufficiently explored. It is still challenging to propose guidance for the design of “three‐in‐one” cathode toward optimal H‐SOFC performance below and above 650°C, with the prerequisite of gaining a comprehensive understanding of the roles of Co and Fe in determining the H‐SOFC performance. This work is to address this challenge. Through theoretical/experimental studies, Co is identified to play a role in improving the oxygen reduction reaction (ORR) activity while Fe plays a role in facilitating the cathode/electrolyte interfacial proton conduction. Therefore, if the operating temperature is above 650°C, lowering the Co/Fe ratio in “three‐in‐one” cathode becomes crucial since the limiting factor shifts from ORR activity to proton conduction. Implementing this strategy, the SOFC using BaCo0.15Fe0.55Zr0.1Y0.1Yb0.1O3−δ cathode achieves peak power densities of 1.67 W cm−2 under H‐SOFC mode at 700°C and 2.32 W cm−2 under dual ion‐conducting SOFC mode at 750°C, which are the highest reported values so far.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".